Dariel Chalas

P DSL NYY Yankees

Age 19 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	18	ROKDSL NYY Yanke…	7	10	11.70	6.70	22.0%	20.3%	—	K 15.0% · BB 25.4% · FIP 7.66
2027PROJ	19	MLBNYY	6	6	5.60	5.60	21.8%	18.2%	-0.1
2028PROJ49% MLB	20	MLBNYY	10	10	5.30	5.18	22.4%	15.5%	-0.1

Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0 WAR median (P10 0 / P90 0, comp-based) · star 0% · didn't stick 99%

CompsAlejandro Lugo (age 18) · Jordy Luciano (age 21) · Isaac Gallegos (age 21)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 140131vR 123

ERA5.60

FIP5.60

K%21.8%

BB%18.2%

K-BB%3.6%

Proj IP6

Value2027 · WAR

Runs saved vs league avg · 6 IP

Grades · Contract

Scouting Grades

K†5055

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to industry-standard fWAR.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2026	18	ROK MLE	DSL NYY Yankees	7	0	10	59	13	12	2	0%	1.4	15.0%	25.4%	-10.4%	4.7%	11.70	7.66	—
2026	18	ROK MLE	DSL NYY Yankees	7	0	10	59	13	12	2	0%	1.4	15.0%	25.4%	-10.4%	4.7%	11.70	7.66	—
2026	18	ROK RAW	DSL NYY Yankees	7	0	10	59	13	12	2	0%	1.4	22.0%	20.3%	1.7%	3.4%	11.70	6.70	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	19	MLB	NYY	6	0	6	25	6	5	1	0%	1.0	21.8%	18.2%	3.6%	3.0%	5.60	5.60	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	20	MLB MLE	NYY	19	0	20	84	19	13	3	0%	1.1	22.4%	15.5%	6.9%	3.0%	5.30	5.18	-0.1
2028	20	MLB CTX	NYY	10	0	10	42	9	7	1	0%	1.0	22.4%	15.5%	6.9%	3.0%	5.30	5.18	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	9	6	1	0%	1.1	22.3%	15.5%	6.8%	3.0%	5.30	4.80	-0.0
/ 200 IP	—	RAW		190	0	200	844	183	122	20	0%	1.1	22.3%	15.5%	6.8%	3.0%	5.30	4.80	-0.6
Career	—	MLE		7	0	10	59	9	15	3	0%	1.4	15.0%	25.4%	-10.4%	4.7%	11.70	7.66	-0.1
/ 200 IP	—	MLE		140	0	200	1180	177	300	56	0%	1.4	15.0%	25.4%	-10.4%	4.7%	11.70	7.66	-1.5

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Dariel Chalas (OGILVIE)	—	—	5.60	21.8%	18.2%	3.0%	—	5.18	22.3%	6.8%	20	-0.42	—	—	—
Alejandro Lugo R 2021 · 4.91 FIP	18	SU	4.91	20.4%	16.7%	2.6%	.265	4.96	16.7%	3.1%	98	+0.05	3.77	159	88
Jordy Luciano R 2022 · 4.97 FIP	21	SU	4.97	24.9%	22.3%	2.1%	.306	5.33	17.1%	-4.8%	80	+0.36	4.97	104	85
Isaac Gallegos R 2024 · 4.40 FIP	21	SU	4.40	22.9%	17.8%	1.8%	.267	3.09	19.9%	10.5%	106	-1.31	2.89	125	85
Michael Perez R 2024 · 5.44 FIP	21	SU	5.44	18.3%	16.1%	3.4%	.296	4.65	23.4%	7.7%	132	-0.79	4.38	153	83
Daniel Lloyd R 2021 · 5.40 FIP	20	SU	5.40	20.4%	22.4%	2.2%	.367	4.15	18.0%	8.5%	226	-1.25	3.59	319	83
Jonathan Jimenez R 2023 · 5.41 FIP	19	SU	5.41	16.4%	16.2%	3.0%	.333	5.09	14.1%	2.2%	178	-0.32	3.49	189	83
Carlos De Los Santos R 2019 · 5.68 FIP	18	SU	5.68	16.9%	16.0%	3.6%	.286	3.95	20.9%	3.2%	86	-1.73	3.67	173	83
Will Varmette R 2024 · 5.06 FIP	21	SU	5.06	22.8%	19.3%	2.6%	.302	5.13	16.1%	2.3%	135	+0.07	4.69	182	83
Brandon Dufault R 2021 · 5.32 FIP	22	SU	5.32	22.1%	15.9%	3.8%	.278	4.83	21.0%	4.2%	66	-0.49	4.38	152	83
Paul Gervase R 2022 · 4.91 FIP	22	SU	4.91	20.3%	16.2%	2.7%	.345	3.76	29.3%	16.0%	152	-1.15	3.38	211	83
Elison Joseph R 2021 · 5.31 FIP	20	SU	5.31	17.4%	19.2%	2.3%	.254	4.55	23.5%	6.8%	133	-0.76	3.32	217	82
Hudson Leach R 2024 · 5.37 FIP	22	SU	5.37	20.5%	20.0%	2.7%	.261	4.54	20.9%	3.1%	71	-0.83	2.77	101	82
Leandro Lopez R 2021 · 6.37 FIP	19	SU	6.37	24.7%	24.6%	4.1%	.222	3.74	25.0%	7.8%	104	-2.63	3.03	273	82
Tommy DeJuneas R 2017 · 4.72 FIP	21	SU	4.72	19.1%	15.5%	2.3%	.357	4.59	20.8%	4.9%	100	-0.13	3.93	178	82
Andrew Schultz R 2019 · 5.25 FIP	22	SU	5.25	20.9%	17.8%	3.0%	.345	4.59	23.0%	4.7%	45	-0.66	3.56	176	82
José Mesa Jr. R 2016 · 5.41 FIP	22	SU	5.41	22.4%	17.2%	3.7%	.311	4.00	22.8%	9.6%	113	-1.41	3.33	176	80
Starlyn Pichardo R 2023 · 4.56 FIP	19	SU	4.56	21.7%	19.3%	1.5%	.298	7.12	19.6%	-10.2%	26	+2.56	4.56	123	80
Greg Weissert R 2016 · 5.22 FIP	21	SU	5.22	19.4%	19.3%	2.4%	.382	3.80	23.0%	10.3%	126	-1.42	2.57	487	80
Marcus Crescentini R 2015 · 5.80 FIP	22	SU	5.80	21.8%	21.9%	3.2%	.365	3.95	23.3%	11.6%	123	-1.85	2.74	150	80
Adonis Villavicencio R 2022 · 4.65 FIP	21	SU	4.65	21.5%	21.9%	1.1%	.316	3.93	18.0%	3.9%	90	-0.72	3.21	115	80